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This study aimed to identify the determinants of farmers' participation in agricultural information-sharing digital groups and their impacts on farm performance.

Primary data of the 2015/2016 crop year collected from 175 cattle farmers were analyzed using descriptive statistics and econometric models. Farmers who had smartphones and participated in social groups/applications, especially those created to exchange agricultural information, were considered adopters of the technology.

A Poisson hurdle model showed that farmers' decision to participate in agricultural information-sharing digital groups is determined by schooling, age (negative effect) and use of tools for planning production. The intensity of participation is affected by risk propensity, interaction with specialist advisors, use of tools for planning production and participation in cooperatives. The authors also found empirical evidence that farmers' participation in agricultural information-sharing digital groups positively affects farm income per hectare.

The results of this study are important for accelerating the diffusion of low-cost digital technologies, which are powerful tools for improving farmers' sharing and access to valuable information in real time and in locations far from urban areas.

To the best of the authors’ knowledge, this is the first empirical analysis of the adoption and impacts of agricultural information-sharing digital groups/applications by Brazilian cattle farmers. The diffusion of simple digital technologies is important for reducing heterogeneity and increasing the efficiency of cattle production.

The aim of this paper is to identify some specificities of production planning and control (PPC) activities in the one-of-a-kind-production (OKP) process through an extensive literature review. Relevant aspects related to systems and PPC activities in the context of OKP environment are discussed, and six opportunities for future research are highlighted.

The following research is based on a review of 53 articles published in peer-reviewed journals over the past three decades. After an initial descriptive analysis based on bibliometric indicators, a cluster analysis of 15 most cited articles was carried out using multivariate data analysis techniques and in-depth analysis.

The results reveal some specificities inherent to the clusters featured in the research, including aspects of planning, control and systems for OKP process. This cluster addresses information regarding next-generation manufacturing systems, scheduling and design science, computer simulation and project approach. On the other hand, the authors point out six topics for future research regarding contemporary issues associated with PPC in the context of OKP.

This paper fills an important gap regarding OKP production planning and control practices. The results provide a theoretical overview of different PPC practices suitable for the OKP environment. Furthermore, it can provide insights for scientific developments in order to manage the complexity inherent in the OKP process.

The versatility of customer relationship management (CRM) systems has kept these technologies popular over the years. These solutions have been integrated into organizations of all sizes, from large corporations to small- and medium-sized enterprises. Similarly, CRM systems have also found applications in all types of industries and business sectors. All this has been the driving force behind the proliferation of CRM solutions around the world. In this chapter, the author not only reflects on the impact and democratization of CRM systems on business management and marketing strategies but also explores how these technologies can determine the company's income. In particular, the author presents an experiment that analyzes the extent to which the volume of annual investment in CRM solutions can be used to predict annual net income in a sample of companies. Using time series analysis and applying the autoregressive integrated moving average modeling technique, the researcher examines a sample of 10 companies from different industries, and countries, over a 20-year period. The results show the efficiency of the predictive models developed in nine of the 10 companies analyzed. The findings of this study allow us to conclude that there seems to be an association between the investments made in CRM solutions and the income of the companies that invest in these technologies.

Mexico is a nation that attracts significant volumes of international tourists annually. The country possesses abundant natural and cultural assets, with significant opportunities for its tourism sector. Its geographical positioning, favourable weather, and the hospitality of its inhabitants enhance these prospects. Simultaneously, this country exhibits a heightened susceptibility to natural calamities and a dearth of public safety measures. The Mexican tourism industry encounters significant challenges within the framework of the VUCA (volatility, uncertainty, complexity, and ambiguity) model. These challenges include the inherent natural risks associated with the country, the escalating impact of global warming, and the proliferation of organised crime. Within this context, the management of tourist destinations in Mexico neglects significant factors highlighted in theoretical models associated with competitiveness and sustainability. These factors include public security, crisis and disaster management, political will, load capacity, and destination’s image. The predicament encountered by Mexican tour operators is formidable, as the socio-political circumstances in Mexico facilitate the expansion of organised crime, leading to its infiltration into various sectors and regions of the country, with significant impacts on tourist operations. This chapter analyses the effects of organised crime on Mexico’s tourism industry, utilising the VUCA framework as a conceptual lens.

The management of consumer privacy has become a critical concern for organizations in the age of artificial intelligence–powered marketing. The impact of data on the market environment has brought both benefits and challenges, with marketers gaining valuable insights but also raising privacy concerns. As artificial intelligence–powered marketing advances, consumer vulnerability increases due to the sensitivity of collected data. This vulnerability leads some consumers to resort to falsifying information, posing a significant threat to the digital economy. Privacy empowerment and customer control play a vital role in addressing these challenges. This chapter explores the influencing factors and ethical considerations surrounding data falsification. It also discusses strategies to mitigate perceived vulnerability through privacy controls and explores the consequences of data breaches and customer vulnerability. The chapter further emphasizes the need for organizations to balance benefits, risks, and customer trust while harnessing the value of customer data. An ethical framework for data privacy marketing audits is proposed to help organizations assess their data practices responsibly and competitively. By integrating personal data protection strategies within an ethical framework, organizations can protect consumer privacy, enhance customer trust, and maintain their competitive edge in the market.

This preliminary study aims to investigate and describe aggression-supportive normative beliefs among patients of a high-secure hospital.

Therapy data from a sample of high-secure forensic hospital patients (N = 11) who had participated in Life Minus Violence-Enhanced, a long-term violence therapy, was examined using interpretative phenomenological analysis (IPA). During therapy, cognitions linked to past incidences of aggression were explored using aggression choice chains.

IPA was applied to data generated through this process to examine the presence and nature of normative beliefs reported, identifying seven themes: rules for aggressive behaviour; use of violence to obtain revenge; processing emotions with violence; surviving in a threatening world; do not become a victim; using violence to maintain status; and prosocial beliefs.

Findings demonstrate that forensic patients have specific aggression-supportive normative beliefs, which may be malleable. Limitations and implications are discussed.

The lean manufacturing (LM) approach is a highly effective method that can be implemented in any industry to streamline production processes, meet customer demand and eliminate any unnecessary waste. This paper aims to propose and evaluate a generic project-based framework grounded on the LM approach for reducing lead time in foundry processes.

Using design science research (DSR), we developed a generic LM project-based framework for reducing lead time in foundry processes.

The developed framework provides an alternative method to implement LM projects to reduce lead time and nonvalue activities in foundry factories.

The findings of this research can guide better lean practitioners for lead time reduction in foundry processes.

This paper contributes to the operational excellence literature when discussing the impact of the LM approach on foundry processes. In addition, the paper provides a roadmap for reducing lead time in a foundry company.

Buying online has become a widespread and common activity for consumers, and, for many organizations, e-commerce has become a very profitable alternative to sell their products and services, also allowing them to leverage their strategy in new geographical markets immediately. Although the literature on the subject is comprehensive, there is a gap in identifying the holistic constructs that are the determinants of consumers' choice of an online store. This research resorts to an exploratory study, based on a nonsystematic literature review, seeking to identify these constructs. The results obtained allowed us to identify the following constructs: consumer behavior, customer experience, web content, catalog, terms and conditions, customer support, perceived value, trust, security and privacy, satisfaction, and loyalty. Customer experience, satisfaction, and loyalty constructs stand out from a strategic perspective.

This study aims to assess how undergraduates’ exposure to entrepreneurship education (EE) may increase their volitional desire and behavioral control to start-up a business.

The model establishes three different paths from EE to entrepreneurial intention (EI): attraction and passion through desire and confidence through control. These paths are assessed by partial least-squares structural equation modeling in a sample of 650 undergraduates from Poland, Turkey and Portugal.

The most effective way by which EE may increase EI is by promoting a favorable change in the attractiveness of the entrepreneurship career. Contrary to expectations based on the literature, the effects of EE on perceived behavioral control are weak and limited to aspects related to financial control.

EE programs should consider desire and control in different phases of training, with the following learning outcomes: explore prospective rewards of an attractive entrepreneurial career, develop self-efficacy regarding management competences and gain control by assuring skills to cope with failure.

To the best of the authors’ knowledge, this study is the first to establish a path from EE to EI through passion and desire. It is also the first to consider entrepreneurial passion as a positive anticipated emotion in the model of goal-directed behavior. The results allow to relate the different paths with different learning outcomes of EE programs.

Realistic composite vehicles with 2, 3, 5 and 9 axles, consisting of a truck with one or two trailers, are addressed in this paper by computational models for vehicle–bridge interaction analysis.

The vehicle–bridge interaction (VBI) models are formed by sets of 2-D rigid blocks interconnected by mass, damping and stiffness elements to simulate their suspension system. The passage of the vehicles is performed at different speeds. Several rolling surface profiles are admitted, considering the maintenance grade of the pavement. The spectral density functions are generated from an experimental database to form the longitudinal surface irregularity profiles. A computational code written in Phyton based on the finite element method was developed considering the Euler–Bernoulli beam model.

Several models of composite heavy vehicles are presented as manufactured and currently travel on major roads. Dynamic amplification factors are presented for each type of composite vehicle.

The VBI models for compound heavy vehicles are 2-D.

This work contributes to improving the safety and lifetime of the bridges, as well as the stability and comfort of the vehicles when passing over a bridge.

The structural response of the bridge is affected by the type and size of the compound vehicles, their speed and the conservative grade of the pavement. Moreover, one axle produces vibrations that can be superposed by the vibrations of the other axles. This effect can generate not usual dynamic responses.